Impacts of landscape patterns of blue-green-gray spaces on summer land surface temperature across multiple grid scales in the Pearl River Delta urban agglomeration
|更新时间:2026-09-20
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Impacts of landscape patterns of blue-green-gray spaces on summer land surface temperature across multiple grid scales in the Pearl River Delta urban agglomeration
Acta Scientiarum Naturalium Universitatis SunyatseniPages: 1-10(2026)
Zheng Kaican, Liao Weilin. Impacts of landscape patterns of blue-green-gray spaces on summer land surface temperature across multiple grid scales in the Pearl River Delta urban agglomeration[J/OL]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2026, 1-10.
DOI:
Zheng Kaican, Liao Weilin. Impacts of landscape patterns of blue-green-gray spaces on summer land surface temperature across multiple grid scales in the Pearl River Delta urban agglomeration[J/OL]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2026, 1-10.DOI: 10.11714/acta.snus.ZR20260113.
Impacts of landscape patterns of blue-green-gray spaces on summer land surface temperature across multiple grid scales in the Pearl River Delta urban agglomeration
Blue-green-gray spaces are principal components of urban underlying surfaces, and optimizing their landscape patterns can significantly mitigate urban thermal risks. However, studies on the impacts of blue-green-gray space landscape patterns on land surface temperature (LST) across multiple grid scales in urban agglomerations remain limited. Therefore, this study selected the Pearl River Delta urban agglomeration as the study area and used land cover data and MODIS LST data for 2022 to investigate how landscape patterns of blue-green-gray spaces affect summer daytime LST across multiple grid scales (i.e., 1, 2, and 3 km) by combining the XGBoost model, SHAP method, and accumulated local effects (ALE) method. Results show that gray space landscape patterns are the primary drivers of LST variation across all scales, whereas the influence of blue and green spaces increases with grid size. In addition, the ALE results indicate that increasing the proportion, patch density, and aggregation of blue and green spaces, reducing the proportion, patch density and aggregation of gray spaces, and reasonably regulating the largest patch size and shape complexity of various spaces can effectively reduce LST. However, the optimal landscape configuration must be determined according to specific spatial scales. The findings provide a scientific basis for optimizing urban landscape patterns and support the sustainable development of urban agglomerations.
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